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2008

Online Boosting Based Intrusion Detection in Changing Environments

8 years 4 months ago
Online Boosting Based Intrusion Detection in Changing Environments
Intrusion detection is an active research field in the development of reliable web-based information systems, where many artificial intelligence techniques are exploited to fit the specific application. Although some detection algorithms have been developed, they lack the adaptability to the frequently changing network environments, since they are mostly trained in batch mode. In this paper, we propose an online boosting based intrusion detection method, which has the ability of efficient online learning of new network intrusions. The detection can be performed in real-time with high detection accuracy. Experimental results show the advantage of the method in the intrusion detection application. Categories and Subject Descriptors K.6.5 [Management of Computing and Information Systems]: Security and Protection--Invasive software (e.g., viruses, worms, Trojan horses), Unauthorized access (e.g., hacking, phreaking); C.2.3 [Computer-Communication Networks]: Network Operations--Network mon...
Yanguo Wang, Weiming Hu, Xiaoqin Zhang
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ICAI
Authors Yanguo Wang, Weiming Hu, Xiaoqin Zhang
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